Romanian Distribution Committee Magazine, Volume 12, Issue 3, Year 2021

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VOL UME12 I S S UE3 2021

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Editorial: Refining the Emotional intelligence, Resilience Thinking, Ingredients of Success, a New Innovation Process, and Crisis as a Learning Experience

In our last RDCM Issue we remembered that a great team consists of great people, proving individual commitment to this team effort of translating to great performance which is so necessary in today’s general environment (every corner of the PESTEL analysis being seriously impacted by COVID-19), at the intersection of digital transformation (caused by the evolving digital technology) and digital entrepreneurship (challenged to work better across time and space, its growth strategy being sustained by customer obsession enabling customer needs’ anticipation and satisfaction, and by prioritization of investments and capabilities helping accelerate this sustainable growth), within the adopted defined, designed and built ecosystem based on clear principles concerning the physical and digital space reflected by the chosen design supporting, one hand, innovation and growth, and on the other hand tangible outcomes in accordance with the shaped value proposition (Purcarea, 2021).

It often happens to find yourself in the situation to present analysis findings (after interpreting the data gathered through the use of analytical and logical reasoning) by sharing undesirable insights, it is important to refine the emotional intelligence (EQ, defined as the ability to understand both, your own emotions, and those of the people around you), considering (as recently recommended by Brenda Ellington Booth, a Clinical Professor of Leadership at the Kellogg School of Management at Northwestern University, and an Executive Coach or EQ) the four components of EQ: (Stone, 2021) self-awareness (the self-check-in, according to Booth); self-management (doing now what is recommendable after the self-check-in); social awareness (trying to better understand people around you, by reading their emotions); relational management (valorizing the above-mentioned assessed social awareness, and making them feel

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motivated and appreciated doesn’t matter the answers received, encouraging the alignment with organizational values).

And as we are always feeling great talking with our experienced, knowledgeable, and well-informed Readers, allow us to move on to the next (but connected) items for today’s discussion (starting from looking before and beyond the COVID-19 crisis), namely: • How companies’ growth can be driven by marketing, the CMOs (supported by CEOs) transforming other leaders (by unifying the C-suite) into champions of their marketing agenda within a company’s operating model supporting cross functional collaboration, as underlined by McKinsey’s representatives (Boudet et al., 2019). The question here is if marketing executives are Unifiers (who report meaningfully more support for and willingness to actively participate in marketing’s agenda from CEOs than Loners, and have the analytics resources they need), Loners, or Friends, as shown in the figure below.

Figure no. 1: Today's CMOs break into three different archetypes Source: Boudet, J., Cvetanovski, B., Gregg, B., Heller, J. and Perrey, J., 2021. Marketing’s moment is now: The Csuite partnership to deliver on growth. [pdf] McKinsey Marketing & Sales Practice, June 2019, p. 3 (work cited)

• How the relation of growth, inclusion, and sustainability at the level of an economy growth model is functioning, these three elements together, according to rigorous research by McKinsey (Padhi et al., 2021) being seen as opening the way to create a new era of sustainable and inclusive growth (see the figure below) in which all stakeholders (governments, businesses, local communities, and individuals) have a reserved role to play.

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Figure no. 2: Sustainable and inclusive growth can be a dynamic, self-reinforcing combination, but achieving it will require addressing counteracting forces Source: Padhi, A., Manyika, J., Madgavkar, A. and Chewning, E., 2021. A sustainable, inclusive, and growing future for the United States. [pdf] McKinsey & Company, November 2021, p. 2 (work cited)

• How resilience (defined by the BCG Henderson Institute, Boston Consulting Group’s strategy think tank, as “a company’s capacity to absorb stress, recover critical functionality, and thrive in altered circumstances”) creates value which increases with crisis frequency, four types of advantage (anticipation, cushioning, adaptation, shaping) being created by the resilient companies (which are deploying specific measures to operationalize the six principles shown in the figure below) so as to help them achieve superior performance in crises (Reeves et al., 2020).

Within this framework, it was underlined the need to avoid the confusion around resilience by educating managers so as to made distinction between resilience thinking (focused on building this critical capability to deliver long-term outperformance, by “coping with and benefiting from the unexpected”, and “modeling and quantifying knowable risks”) and efficiency thinking.

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Figure no. 3: Design Principles to Increase Resilience Source: Reeves, M., Nanda, S., Whitaker, K. and Wesselink, E., 2020. Becoming an All-Weather Company, BCG, September 09 (work cited)

• How to dissect the business resilience ante and post-pandemic, taking into account the conclusions logically supported highlighted recently (in an article published in the European Business Review) by the by the well-known Professor Jacques Bughin (and former Director of the McKinsey Global Institute) and Francis Hintermann, Global Managing Director of Accenture Research, who stated: “What those crises (A/N, the 2000 internet bubble burst and the 2008 financial subprime collapse) have also taught us, is that the most complex challenge is recovering from the missed growth opportunities during the collapse … And the key issue is how covid-19 has built a profit bifurcation between the 30% recovered and the other 70% of firms… Evidently, the distribution of recovery is likely to span over the three scenarios, and the main message is the likely important bifurcation between the have (rebounded) and the have not. How can then one firm avoid to be on the wrong side of the bifurcation? … Given the four ingredients (innovation, ecosystem play, twin transformation, and agility), they might also be different ways to combine and manage for resilience … Clearly, the first thing a manager must recognize is that the effect of sudden crises can be such that every company may have to develop enough organizational ability to ensure they can quickly reallocate resources… Finally, in general, the synergies among all those ingredients are the little secret for outsized success: digitization has facilitated the emergence of platform-based ecosystem; innovative products have made sustainability a profitable path, and agility has been boosted by digital protocols such as DevOps and others.

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The play is as much about excellence in capabilities as in excellence in the best capability portfolio play.” (Bughin and Hintermann, 2021).

• How to navigate the innovation landscape – within the digital transformation, Artificial Intelligence (AI), Machine Learning (ML), and other technology programs (in many companies) accelerated by the crisis – according to Tony Ulwick, the pioneer of Jobs-to-be-Done Theory (the inventor of the Outcome-Driven Innovation®/ODI process, and the founder of Strategyn, called “the Deming of innovation” by Professor Philip Kotler, The Father of Modern Marketing, and credited with “bringing predictability to innovation” by Harvard Business School Professor Clayton Christensen, The Architect of Disruptive Innovation): “Innovating during COVID-19 is all about customer needs discovery. Companies naturally react to crises by preparing for the worst and hoping for the best… The companies who win in a time of crisis are those who are first to effectively understand and address their customer’s changing needs… Where do you begin? With a new innovation process… Adopt an outcome-driven mindset when it comes to understanding customer needs… Apply this mindset to your markets of interest. Businesses can obtain deep customer insights in days through virtual customer interviews… Act on the insights” (Ulwick, 2021).

• How essential is to remember key details of lessons learned but forgotten while continuing on a growth path (so as to avoid underestimating the importance of organizational factors in translating a growth strategy into reality), going beyond the strategic side of growth (Dewhurst, Heywood and Rieckhoff, 2011): “Growth naturally creates new interactions and processes, expected and unexpected, and often at a fast pace. To manage them, the employees who face the greatest complexity—for example, those in functions or businesses that will see increased activity— must have “ambidextrous” capabilities. These enable people to take initiative beyond the confines of their jobs, to cooperate and build linkages across the organization, and to complete many tasks in parallel. Companies sometimes forget to think about these capabilities in the units immediately involved in growth and very often don’t do so beyond them”.

• How to build connective tissue in the transformation work to be performed (going beyond agile teams), by driving change across all five elements of the companies’ operating model (strategy, structure, process, people, and technology), new McKinsey research (Aghina et al., 2021) revealing that a highly successful transformation allows an organization to overtake born-agile organizations by measures such as operating-model maturity (as shown in the figure below), and considering both company-specific unique factors (such as context and quality of execution), and a by McKinsey identified four-step recipe to boost chances of success.

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Figure no. 4: Agile operating-model maturity is measured across 17 elements, and a successful transformation significantly increases an organization’s score. Operating-model maturity score out of 5, by state of change Source: Aghina, W., Handscomb, C., Salo, O. and Thake, T., 2021. The impact of agility: How to shape your organization to compete. [pdf] McKinsey & Company, Organization Practice, p. 9 (work cited)

Figure no. 5: Design Principles to Increase Resilience Source: Reeves, M., Nanda, S., Whitaker, K. and Wesselink, E., 2020. Becoming an All-Weather Company, BCG, September 09 (work cited)

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• How in adversity during COVID-19 a resilient company can combine, according to BCG (Reeves, Shmul and Zuluaga Martínez, 2021), three components of performance (lower shock impact, faster recovery speed, and greater recovery extent, as shown in the above figure) driven by the above-mentioned four competitive advantages, turning COVID-19 impact into opportunities for growth (not focusing only on reducing this impact), by valorizing dynamic capabilities and influencing customers’ and partners’ ecosystems to redefine industry standards to their long-term advantage.

Finally, we would also like to bring to our experienced, knowledgeable, and wellinformed Readers’ attention the fact that in a very recent article published in European Financial Review by the renowned Professor, Global Thought Leader, Consultant, and bestselling author, David De Cremer (2021), underlined how important is for a company and its employees to use crisis as a learning experience in dealing with a changing environment based on employees’ new behavior of adapting and bringing new perspectives accordingly: “In times of crisis, companies have no choice other than to face themselves in the mirror and ask what is needed to survive…

Crisis situations have in common that once the crisis is over, the business environment will have undergone changes and most likely adopted new ways of working. If one then failed to adopt a mindset to move forward and adapt, companies will find themselves falling behind.”

Theodor Valentin Purcărea Editor-in-Chief References Aghina, W., Handscomb, C., Salo, O. and Thake, T., 2021. The impact of agility: How to shape your organization to compete. [pdf] McKinsey & Company, Organization Practice, pp. 3, 9, 12-13. Available at: <The-impact-of-agility-How-to-shape-your-organization-to-compete-v4.pdf> [Accessed at 12 November 2021].

Boudet, J., Cvetanovski, B., Gregg, B., Heller, J. and Perrey, J., 2021. Marketing’s moment is now: The C-suite partnership to deliver on growth. [pdf] McKinsey Marketing & Sales Practice, June 2019, pp. 3, 5, 7-8. Available at: <marketings-moment-is-now-the-c-suite-partnership-todeliver-on-growth.pdf> [Accessed at 14 November 2021].

Bughin, J. and Hintermann, F., 2021. Breaking Down Business Resilience, Post-Pandemic: The Data Reveal Surprises—and a Blueprint for Moving Forward, European Business Review, October 29, 2021. [online] Available at: <https://www.europeanbusinessreview.com/breaking-downbusiness-resilience-post-pandemic-the-data-reveal-surprises-and-a-blueprint-for-moving-forward/> [Accessed at 10 November 2021].

De Cremer, D., 2021. When Survival is on the Line, Can Rebels be the Solution? European Financial Review, November 9. [online] Available at: <https://worldfinancialreview.com/when-survival-is-on-the-line-can-rebels-be-the-solution/> [Accessed at 15 November 2021].

Dewhurst, M., Heywood, S., and Rieckhoff, K., 2011. Preparing your organization for growth. [pdf] McKinsey Quarterly, Organization Practice, May 2011, pp. 1,5. Available at: <preparing your organization for growth.pdf> [Accessed at 14 November 2021].

Padhi, A., Manyika, J., Madgavkar, A. and Chewning, E., 2021. A sustainable, inclusive, and growing future for the United States. [pdf] McKinsey & Company, November 2021, p. 2. Available at: <a-sustainable-inclusive-and-growing-future-for-the-united-states-final.pdf> [Accessed at 9 November 2021].

Purcarea, T., 2021. Business-Educational Partnership, Doing Work Better Across Time and Space, Integrating the Growth Triple Play, and Teamworking for Performance, Romanian Distribution Committee Magazine, vol. 12(2), August.

Reeves, M., Nanda, S., Whitaker, K. and Wesselink, E., 2020. Becoming an All-Weather Company, BCG, September 09, 2020. [online] Available at: <https://www.bcg.com/publications/2020/how-to-become-an-all-weather-resilient-company> [Accessed at 15 November 2021].

Reeves, M., Shmul, Y. and Zuluaga Martínez, D., 2021. How resilient businesses created advantage in adversity during covid, BCG, November 04, 2021. [online] Available at: <https://www.bcg.com/publications/2021/how-resilient-companies-created-advantages-in-adversity-during-covid> [Accessed at 15 November 2021].

Stone, E., 2021. 4 Components of Emotional Intelligence, Kellogg Insight, November 03, 2021, insight@kellogg.northwestern.edu.

Ulwick, T., 2021. How to find growth opportunities in times of crisis, Strategyn, November 10, 2021. [online] Available at: <https://strategyn.com/how-to-find-growth-opportunities-in-times-of-crisis/> [Accessed at 10 November 2021].

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Information and Communications Technology is Merging Data Science and Advanced Artificial Intelligence Towards the Core of Knowledge Based Society -Part 3-

Prof. Eng. Ph.D. Victor GREU Abstract The paper analyses the context and the trends of the actual role/phase of information and communication technology (ICT) advances, for enabling a further progress of the Information Society (IS) towards the Knowledge Based Society (KBS), i.e., to reach a sustainable general development and in the same time avoid undesired evolutions of the Earth ecosystem challenges, like climate changes, Earth resources fading or … Covid 19 pandemic (without forgetting …food!). Observing that “evolutions” also suppose now (looking just at climate changes or Covid 19 daily consequences) a time critical race, we have emphasized the point where the ICT performances (as speed) meet the need for faster solving/processing the complex problems which actually are associated with the Data Deluge (Big Data), produced at the Earth scale, but complicatedly linking a diversity of domains. This way it is revealed the support expected from the ICT advances, where AI became the most promising instrument to face the complex problems of practically all domains, mainly by machine/deep learning (ML/DL) new models and algorithms, based now on Data Science (DS).

Consequently, it is essential to deeper analyse how DS/AI/ICT could work together for better and faster results, providing the expected benefits on refined knowledge, but keeping low the undesired consequences such exponentially development could induce when facing challenges like climate changes and Earth resources fading (as most prominent and increasing every day).

As concrete results of the support for AI gigantic networks, we have presented some issues regarding mechanisms and the core of the relations between the peaks of advanced processors technology and the fundamentals of their limiting factors, including the “46,225 square millimeters” chip that boasts 2.6 trillion transistors, which is in fact the maximal available (entire wafer of silicon) today. These mean that physical limits of technology and also Moore’s Law, we repeatedly have mentioned [18][12], are one of the fundamental challenges for ICT, needing revolutionary innovations in order to go on. This way it is explained why these performances are needed for the most advanced actual and future applications areas of AI, confirming the dramatic struggle of actual ICT trends, to achieve bigger chips, but, in the same time, the dimension of this permanent challenge. The benefic results of AI come along with performant processing (IT), but some of the most complicate optimization problems and eventually AI applications could be found in a diversity of areas of the communications field, although here they appear less impressive than self-driving cars industry, but it is worth

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to recall the crucial importance and the huge dimension of communications when converging with IT in ICT. On this line, among others, some promising AI applications, as in wireless communications and intelligent selfdriving networks, are also presented.

The analysis shows that the general progress of AI/ICT is more and more depending on models and algorithms, confirming also our earlier opinion that the technology advances themselves are not enough, even with the exponential development of hard components of ICT, but they have to be applied considering at every step the refined knowledge that reflects all ICT impact consequences, the fast-changing Data Deluge and the general IS/KBS context at Earth scale. In order to find the optimal matches, a lot of work has to be done on high amounts of available (but usually unstructured) data, but this could be time and energy consuming and this way we have arrived to the core of the relation between the processors performances and the targets of DL/ML/AI, where DS is coming with the expected support, including appropriate methods and algorithms. Each of these methods supposes a deeper approach, which is required to provide the progress in this complex context of AI/ICT/IS/KBS, for better results against more and more difficult actual and future problems at Earth scale.

Predictive causal analytics have to consider the premises/causes of involved processes evolutions we have to predict, while the prominent actual method is still represented by prescriptive analytics, as it provides the highest results we are expecting, i.e., to have the optimal decisions after analyses and prediction of the targeted process/context. For example, this method will be benefic for the self-driving cars industry, when deciding what to do in the everchanging complicate traffic processes. All these methods are important and must work together on the general context and this is also true for both machine learning for making predictions (ML-MD) and machine learning for pattern discovery (ML-PD). The applications of ML-MD are based on previous (historical records) relevant data (supervised learning), while ML-PD are following the unsupervised models, where the ML system is looking to find hidden patterns for predictions [2]. One conclusion is that ML-PD and prescriptive analytics could better support the most AI advances in the future more and more complex context to be optimized, in presence of the high levels of uncertainty.

A deeper analysis revealed, considering the first section of the paper, that the DS/AI advances have the potential to improve the general context of ICT/IS/KBS, but the maximal results should necessarily include refined knowledge on multi-criteria optimization. This way, the link between DS/AI advances and the mechanisms of refining knowledge is naturally provided by the updated cyberinfrastructure, which could provide not only the mentioned support of the technology, but also the main level (science and engineering research) and channel to create and spread knowledge and eventually refined knowledge, with maximal efficiency. Research is identified and recognized as the top level of creating and refining knowledge at World scale, it eventually pushing its results everywhere, but the point is that, this way, DS/AI, through cyberinfrastructure, could speed up and enable more efficient the progress of all human activities. One of the most important requirements to be fulfilled in the exponential evolution of the DS/AI/ICT context, in order to get optimized solutions and refining knowledge for the actual challenges involving Big Data and other complicated problems of the Earth ecosystem is the need of standardization when developing such complex and advanced cyberinfrastructures, aiming to provide efficient interoperability and development.

For knowledge refining, other features have to be also considered, because, in all cases where human mind is involved in the Earth ecosystem (knowledge must be studied in a particular context), the role of human intelligence is and must remain fundamental even in the DS/AI advances context, including the revealed link of knowledge with learning. In the same time, it is recognized that refining knowledge is a difficult and critical process of obtaining added value, where DS/AI and ICT will leverage knowledge towards the core of knowledge based society.

We argued that if this knowledge is properly associated with human intelligence and innovative actions, sometimes an added value could come from it more than from technology. Using this idea and the digital transformation/disruption trends, we could witness miracle changes of the business models, based on human potential and labor but using ICT advances with unprecedented efficiency. Presenting some simple examples, another iceberg tip of ICT was revealed, as indeed they forecast a new World, which will surprise us not mainly by the technology advances, but especially by the ways ICT could leverage the innovation in the modes of impacting the human thinking and of using ICT when refining knowledge.

The final conclusion is that we have to timely watch and analyse DS/AI and generally the ICT advances, in order to optimally achieve the refined knowledge that could provide the sustainable progress of IS/KBS. Keywords: Data Deluge, Big Data, knowledge refining, data science, artificial intelligence, prescriptive analytics, machine/deep learning, wafer of silicon, Self-Driving Networks JEL Classification: L63; L86; M15; O31; O33

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“The only true wisdom is in knowing you know nothing” ― Socrates

1. Data Science and future artificial intelligence From their first steps, humans tried to shorten their path toward reaching what they are looking for (beginning with food), but the World evolution created so many paths and so many purposes, as today is more and more difficult to think at all of them in the same time.

We could say that space and time are only the most prominent dimensions where our intelligence has to better perform, but is clear that although we have reached to “step” on other planets and the computers speeds hide from our usual perception unprecedented time divisions, space and time are far from being our only actual optimization goals when facing World challenges like climate changes, Earth resources fading or … Covid 19 pandemic (without forgetting …food!).

Still, time and a huge diversity of paths generalizing the “space” are the core of performances we have to improve, but it is more than obvious that today this is really not possible to conceive that without the crucial support of the information and communication technology (ICT), which generally became, by its services, products, applications and systems, the main driving factor of the Information Society (IS) towards the Knowledge Based Society (KBS).

In fact, as many other human visions on life progress, the idea of generally improving (time, space etc.) performances is also going to be not enough accurate, just because of the actual complexity and performance levels we have to face, in almost all domains of ICT/IS/KBS, in order to finally obtain the knowledge and further the refined knowledge which have to reflect the exponential development and impact of ICT on Earth ecosystem.

This way we can better understand the actual role/phase of ICT advances, for enabling a further World progress, in all areas, i.e., to reach a sustainable general development and in the same time avoid catastrophic evolutions of the mentioned Earth ecosystem challenges.

Step by step, considering that “evolutions” also suppose now (looking just at climate changes or Covid 19 daily consequences) a time critical race, we have just arrived to the point where the ICT performances (as speed) meet the need to faster processing of the complex problems which actually are associated with the data deluge (Big Data), produced at the Earth scale, but complicatedly linking a diversity of domains.

Here comes the support expected from the ICT advances, where AI became the most promising instrument to face the complex problems of practically all domains, by machine learning (ML) or deep learning (DL) new models and algorithms, based now on Data Science (DS) [3][9].

Consequently, it is essential to deeper analyse how DS/AI/ICT could work together for better and faster results, providing the expected benefits on refined knowledge, but keeping low the undesired consequences such exponentially development could induce when facing challenges like climate changes and Earth resources fading (as most prominent and increasing everyday) [18].

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The ways DS, AI and generally ICT may be developed and optimized on complex criteria could be observed by some relevant cases, intended to relieve the intimate relations of these interdependent domains of ICT/IS/KBS and further the main directions of improvement.

Perhaps a recent technology achievement could bring a straightforward picture of these complex dependences, actually linking the core of ICT with the peaks of DS/AI [1]: << Almost from the moment Cerebras Systems announced a computer based on the largest single computer chip ever built, the Silicon Valley startup declared its intentions to build an even heftier processor. In April, the company announced that its next-gen chip, the Wafer Scale Engine 2 (WSE-2), will be available in the third quarter of this year. WSE-2 is just as big physically as its predecessor, but it has enormously increased amounts of, well, everything. The goal is to keep ahead of the ever-increasing size of neural networks used in machine learning. “In AI compute, big chips are king, as they process information more quickly, producing answers in less time—and time is the enemy of progress in AI,” Dhiraj Mallick, vice president of engineering and business development, said in a statement.>> This amazing achievement (boasts 2.6 trillion transistors) is relevant not only by “enormously increased amounts of, well, everything” needed in the most advances domain of AI, but here the main direction of actually improving AI it is pointed (ever-increasing size of neural networks used in machine learning) and also is time, as the limiting factor (enemy) of “progress in AI”.

More than these, we could have this way a flavour about the mechanisms and the core of the relations between the peaks of advanced processors technology and the fundamentals of their limiting factors: “Training neural networks takes too long—weeks for the big ones when Andrew Feldman cofounded the company in 2016. The biggest bottleneck was that data had to shuttle back and forth between the processor and external DRAM memory, eating up both time and energy.”

Now it is obvious why these performances are needed for the most advanced actual and future applications areas of AI: “With gigantic networks for natural-language processing, image recognition, and other tasks on the horizon, you’d need a really big chip. How big? As big as possible, meaning the size of an entire wafer of silicon (with the round bits cut off), or 46,225 square millimeters.”

Finally, we may also understand the dramatic struggle of actual technology to achieve “a really big chip”, but, in the same time, the dimension of this permanent challenge launched

by AI: “How big? As big as possible, meaning the size of an entire wafer of silicon”.

In addition, we have to point that “46,225 square millimeters” is in fact the maximal available (entire wafer of silicon) today, meaning that physical limits of technology and also Moore’s Law, we repeatedly have mentioned [18][12], are one of the fundamental challenges for ICT, needing revolutionary innovations in order to … go on!

That is why the progress of AI/ICT/IS/KBS has to be supported also by other leveraging factors of the context, as DS is.

Still, it is important to see how DS will further be developed to provide the maximal results associated with every phase of AI/ICT/IS/KBS and correlated with the Data Deluge (Big Data), as it is approached by [2]:

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“The main focus was on building a framework and solutions to store data. Now when Hadoop and other frameworks have successfully solved the problem of storage, the focus has shifted to the processing of this data. Data Science is the secret sauce here. All the ideas which you see in Hollywood sci-fi movies can actually turn into reality by Data Science. Data Science is the future of Artificial Intelligence…”

In reality, the way from fiction to concrete results is long, even with the usual high speed of AI/ICT, due to the complex context of Data Deluge and consequently this have to be step by step analysed: “Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. But how is this different from what statisticians have been doing for years? The answer lies in the difference between explaining and predicting.”

From the beginning we have to observe that the general progress of AI/ICT is more and more depending on models and algorithms, confirming also our earlier opinion that the technology advances themselves are not enough, even with the exponential development of hard components of ICT, but they have to be applied considering at every step the refined knowledge that reflects all ICT impact consequences and the general IS/KBS context at Earth scale [3][12].

In fact, it is clear that the power of hard (ICT) could not be exploited without the appropriate advances of the models and algorithms, which have to also match the applications and the fast-changing Data Deluge context.

In order to find the optimal matches, a lot of work has to be done on high amounts of available (but usually unstructured) data, but this could be time and energy consuming and this way we have just arrived to the core of the relation between the processors performances and the targets of DL/ML/AI, where DS is coming with the above-mentioned expected support as it is further explained: “… a Data Analyst usually explains what is going on by processing history of the data.

On the other hand, Data Scientist not only does the exploratory analysis to discover insights from it, but also uses various advanced machine learning algorithms to identify the occurrence of a particular event in the future. A Data Scientist will look at the data from many angles, sometimes angles not known earlier. So, Data Science is primarily used to make decisions and predictions making use of predictive causal analytics, prescriptive analytics (predictive plus decision science) and machine learning.”

Each of these methods supposes a deeper approach, as all the progress in this complex context of AI/ICT/IS/KBS is naturally requiring for better results against more difficult actual and future problems at Earth scale.

Predictive causal analytics have to consider the premises/causes of involved processes evolutions we have to predict.

The prominent actual method is still represented by prescriptive analytics, as it provides the highest results we are expecting, i.e., to have the optimal decisions after analyses and prediction of the targeted process/context. For example, this method will be benefic for the self-driving cars industry, when deciding what to do in the everchanging complicate traffic processes.

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As it is easy to suppose, all these methods are important and must work together on the general context and this is also true for both machine learning for making predictions (MLMD) and machine learning for pattern discovery (ML-PD).

The applications of ML-MD are based on previous (historical records) relevant data (supervised learning), while ML-PD are following the unsupervised models, where the ML system is looking to find hidden patterns for predictions.

A usual algorithm used for pattern discovery is clustering [2], which aims to identify, in absence of previous relevant data, the solutions that fit the context/process. Examples of such applications could include transport, placement or distribution processes, irrespective the objects or entities involved, which could apply to energy, materials, values or … signals/information.

We can observe that finally ML-PD and prescriptive analytics could better support the most AI advances in the future more and more complex context to be optimized, in presence of the high levels of uncertainty.

A deeper step of the analysis could provide concrete applications examples of DS/AI methods, algorithms and achievements, above presented.

Some of the most complicate optimization problems and eventually applications could be found in a diversity of areas of the communications field, although here they appear less impressive than self-driving cars industry, but it is worth to notice from the beginning the crucial importance and the huge dimension of communications converging with IT in ICT. A relevant approach of such applications, just as a signal for the potential of DS/AI in these communications areas, is given in [4]: “The six papers in this special section address the application of artificial intelligence, machine learning, and data analytics at different layers and different applications of different types of communications networks. The objective of using these tools is the optimal design and improved operation of networks. These articles feature new opportunities to develop and advance various areas of communications through the use and applications of AI/ML/ deep learning technologies.

Research in artificial intelligence (AI) has been active for several decades, but lately, and with the exponential increase in the amounts of available data, new directions of AI, such as machine learning (ML) and data analytics that learn from data, have emerged and have impacted many fields in science and engineering.”

Although a new and not very much extended area of communications, Spectrum Intelligent Radio, just fits the above-mentioned prescriptive analytics methods of DS/AI, as it is given by [4][5]: <<The first article, “Spectrum Intelligent Radio: Technology, Development, and Future Trends,” is authored by P. Cheng, Z. Chen, M. Ding, Y. Li, B. Vucetic, and D. Niyato, and deals with machine learning applications at the physical layer in wireless networks. The article addresses the significant spectrum strains imposed by information collection and decision making in Industry 4.0, which is also known as the fourth industrial revolution. The article focuses on machine-learning-based intelligent radios as a viable solution to this problem and proposes a new radio architecture consisting of three hierarchical forms: perception, understanding, and reasoning. The purpose of these three forms is accurate

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spectrum sensing, accurate prediction of primary users' coverage, and optimal idle channel selection.>> A larger view of the wireless networks, with impact in the huge and emergent IoT, is also presented as an optimal solution for the massive areas of sensors, which will cover the Earth, including self-driving cars complex context [4] [7]: <<The second article, “Toward an Intelligent Edge: Wireless Communication Meets Machine Learning” by G. Zhu, D. Liu, Y. Du, C. You, J. Zhang, and K. Huang, also deals with wireless networks in an environment with massive numbers of edge devices that collect data and upload this data to edge servers that learn from the data and distill intelligent decisions. Examples of such scenarios include sensors in IoT networks, auto-driving cars, and so on. The article proposes a framework that includes a set of new design guidelines for wireless communications in edge learning, which is referred to as learning-driven communication. The article discusses research directions emerging under this framework and provides illustrative examples that cover key communication aspects including multiple access, resource allocation, and signal encoding.>> On the other hand, we suppose that a relevant corollary of the above DS/AI methods and algorithms, along with the unprecedented increase of the complexity in communications networks, the advanced model of Intelligent Self-Driving Networks could be considered [4] [8]: <<The fifth article, “Machine Fault Detection for Intelligent Self-Driving Networks,”

by H. Huang, L. Zhao, H. Huang, and S. Guo, deals with self-driving networks (SelfDNs), which are autonomous networks that are capable of making predictive and adaptive responses to their environment. The article focuses on fault detection in SelfDNs, and proposes a new fault detection architecture for SelfDNs. Under this architecture, an algorithm, named Gaussian Bernoulli restricted Boltzmann machines (GBRBM)-based deep neural network with autoencoder (i.e., GBRBM-DAE), is proposed with the objective of transforming the fault detection problem into a classification problem. Several classification mechanisms are considered and compared using traces from real-world experimental results, and it is shown that the proposed algorithm outperforms other popular machine learning algorithms, such as linear discriminant analysis, support vector machine, and pure deep neural network.>> It is now obvious that some of the most efficacy and needed impact applications of the DC/AI advances will be in the areas of communications, without mentioning the complex interdependent relations and mechanisms which will transfer the benefic consequences of such applications towards all integrated products, services and systems of the ICT context and eventually towards IS/KBS. More than these, above all achievements and promising perspectives, we have to notice that the overall results of using DS and AI will provide in fact the needed knowledge in all fields of activity and eventually the refined knowledge to support a sustainable progress at Earth scale and generally for humankind evolution.

In spite of the complexity revealed by the above examples, the highest challenge will come just when approaching the refined knowledge complicate processes, where the diverse criteria and context dynamic will be the hardest conditions to face.

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2. Refining knowledge as best of knowledge we could actually have Perhaps the most relevant way to link the above-mentioned achievements and promising perspectives of DS/AI with the fundamental need of sustainable progress of IS toward KBS, including the wellbeing of the human race on Earth, by providing at every step of DS/AI/ICT development the necessary refined knowledge, is to come back to the crucial impact of communications in this complex and dynamic context.

With simpler words, we have to recall the role of communications, irrespective the historical phase of human evolution we could consider, but especially when they contributed more and more to expand the information and knowledge that promoted the unprecedented progress of humanity in every activity field, either by books, phones or Internet – to mention just some of the milestones.

As we have already repeatedly presented [21][22], the advances of communications provided the multiplication of the useful information/knowledge, including innovation and best practice everywhere.

If such observations could be considered already obvious, as we are used with the enabling role of communications, this is just the floor where the Data Deluge (Big Data) just exploded, creating for the ICT/IS/KBS context one of the most prominent challenges to be analysed and optimally solved [17][16][21][22].

A deeper analysis could reveal, considering the above section of the paper, that the DS/AI advances have the potential to improve the general context of ICT/IS/KBS, but the maximal results should necessarily include refined knowledge on multi-criteria optimization.

This way, the link between DS/AI advances and the mechanisms of refining knowledge is naturally provided by the updated cyberinfrastructure [16][9], as it is also confirmed by [10]: “A confluence of technology-push and science and engineering research-pull activities and possibilities makes this the right time. Researchers are ramping up their use of computing resources, starting to store enormous amounts of information, and sharing it. Distributed computing, large clusters, data farms, and broadband networks (typified by Internet, Grid and Web Services directions) have moved from research to practical use. We anticipate a phase change, where direct attention to this opportunity can have a highly desirable and nonlinear effect” Here we have to observe not only the mentioned support of the technology, but also the identification of the main level (science and engineering research) and channel to create and spread knowledge and eventually refined knowledge with maximal efficiency.

Research (Science and Engineering) is identified and recognized as the top level of creating and refining knowledge at World scale, it eventually pushing its results everywhere, but the point is that, this way, DS/AI through cyberinfrastructure could speed up and enable more efficient the progress of all human activities.

Although not very new, this signal of the (National Science Foundation=NSF) is more and more actual as the object of these observations, DS/AI/ICT and Big Data context, is advancing as complexity and potential impact: “Effective use of cyberinfrastructure can break down artificial disciplinary boundaries, while incompatible tools and structures can isolate scientific communities for years. Groups are building their own application and middleware software without awareness of comparable

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needs elsewhere, both within the NSF and across all of science. Much of this software will be of limited long-term value absent a consistent computer science perspective. Time and talent will be wasted that could have led to much better computing and much better science. Dramatic changes are coming in computing and application architectures; lack of consideration of work in other sciences and in the commercial world could render projects obsolete before they deliver. Much of the effort under way to use cyberinfrastructure for collaborative research is not giving adequate attention to sociological and culture barriers to technology adoption that may cause failure, even after large investments. The time is ripe for NSF to accelerate the revolution for the benefit of society.”

Covering the Earth ecosystem, when observing also the sociological and culture barriers to technology adoption, this vision is more than a signal due to the practical indirect hints and to the identification of the fundamental relation between DS/AI/ICT and the processes where knowledge could be optimally created and refined (share insights, software, and knowledge, to reduce wasteful re-creation and repetition): „We envision an environment in which raw data and recent results are easily shared, not just within a research group or institution but also between scientific disciplines and locations. There is an exciting opportunity to share insights, software, and knowledge, to reduce wasteful re-creation and repetition. Key applications and software that are used to analyze and simulate phenomena in one field can be utilized broadly. This will only take place if all share standards and underlying technical infrastructures.”

Here we have to notice one of the most important requirements to be fulfilled in the exponential evolution of the DS/AI/ICT context, in order to get optimized solutions and refining knowledge for the actual challenges involving Big Data and other complicated problems of the Earth ecosystem: the need of standardization when developing such complex and advanced cyberinfrastructures, aiming to provide efficient interoperability and development.

More than these, as we also presented [18], an inherent (but less desired) feature of the exponential evolution of the ICT, concerning market size and technological risks, is confirmed pointing the same crucial role of refining knowledge: “Although many of the mechanisms to support the best scientific computing are becoming available through commercial channels, there continue to be special needs that the commercial sector is unlikely to meet directly because of the market size and technological risks. Scientists must have easy access to the finest tools from the commercial and advanced research sectors, without dampening their creativity and ardor to do even better. Individual researchers expend too much effort, frequently with insufficient knowledgeable computing assistance, to create and re-create computing resources; to access, reformat, and save information; to protect the data and software assets.”

In a simpler expression, we have to watch over all consequences of ICT fast pace, as the time for evaluate the long-term impact on IS/KBS is very short, considering the everincreasing complexity of this context, i.e., the refining of knowledge should include the sustainable solutions for ICT/IS/KBS development and Earth ecosystem.

That is why refining knowledge and generally the optimal evolution of IS toward KBS are easier said than done and consequently a complex problem and a subject of timely analyses.

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Perhaps the difficulty of refining knowledge comes first just from itself, as it is recognized that generally knowledge is a dynamic concept, repeatedly analysed [18][12] and largely debated [10][19][13][20], while refining knowledge is consequently even more complicated to be precisely defined, as it also confirmed and detailed by [11]: <<In this paper, the relationship between information and knowledge travels in both directions: knowledge is made explicit and becomes information, while information is internalized and becomes knowledge …The distinction between tacit and explicit is probably the one most frequently referred to in the knowledge management literature … For Polanyi (1962, p. 601-602, emphasis in the original) any activity has two dimensions of knowledge: (1) knowing a thing by attending to it, in the way we attend to an entity as a whole and (2) knowing a thing by relying on our awareness of it for the purpose of attending to an entity to which it contributes. The latter knowledge can be said to be tacit… We may call “knowing by attending to” a focal knowing, and “knowing by relying on” a subsidiary knowing…What is subsidiarily known is tacitly known; but it seems appropriate to extend the meaning of “tacit knowing” to include the integration of subsidiary to focal knowing…>> If these opinions could initially appear only theoretical issues, far from the practical problems of optimization we have mentioned above, here we could notice that the intimate mechanisms of generating knowledge and the fluent relations with data and information, through the human perceptions and actions, are more actual and useful as the circle of ICT innovation and its impact on IS/KBS, we have also presented[12], is faster changing in a complex context, where humans are in the same time causes and consequences (for the purpose of attending to an entity to which it contributes): << Firstly, knowledge is embodied in the individual and secondly, as a consequence, knowledge must be studied in a particular context. The individual processes the data, the information, and adds to the information his/her own previous knowledge, beliefs, values, etc.

In Piaget’s terms, the schemata are in the human mind, and it is in the human mind that the schemata have to adapt to new realities. Knowledge is something that one constructs by him/herself in an interaction with the environment and with others. Articulated explicit knowledge is, therefore, public in the sense that it is accessible to anyone who can understand the code in which it is written, as opposed to knowledge that is private (such as tacit knowledge), which is only inside one’s head. In other words, knowledge becomes information when it is made explicit. Explicit knowledge and specific information, as defined by Mårtensson (2000), are two sides of the same coin. When I am writing, or talking, I articulate my knowledge; that is, I am “externalizing” tacit knowledge into explicit knowledge. However, the receptor of my explicit knowledge, in this case the patient reader, is reading information, and only if s/he adapts (assimilates or accommodates) this information into his/her schemata or theory will the information become knowledge.>> Here we can easily recognize not only the scientific and technical processes of ICT evolution where information and knowledge are generated, but in all cases where human mind is involved in the Earth ecosystem (knowledge must be studied in a particular context), because the role of human intelligence is and must remain fundamental even in the DS/AI advances context, as we have also presented [9] and now detailed and further confirmed: <<This knowledge acquisition process is, therefore, an individual process, since it is the reader who will or will not process the information read. Knowledge, by definition, is in

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someone’s head, and when it is not in someone’s head it is information or data ... Further, it is important to note that the information can never be a perfect replica of the knowledge the individual has, and different individuals will have different ways of approaching the same information ... The different terms and differentiations that knowledge management literature has provided in the conceptualization of knowledge have been presented. Knowledge is in people’s heads, it differs from information or data, it is individual, and in some instances it can be made public or shared as information. In addition, the difference between various types of knowledge has been explained in terms of content. Andriessen (2006, p. 97) identifies six different metaphors in his analysis of the treatment of knowledge in key publications of the knowledge management field: knowledge as something physical, as a wave, as a living organism, as thought and feelings, as a process and as a structure.>> It is important to notice that such detailed and intimate features of the ways to perceive the data, information and eventually achieve associated knowledge, beyond the real benefic impact on all human activity fields we have also mentioned [12], could be useful instruments of better designing and exploiting the AI/ICT products, applications, services and systems, just due to the better understanding of knowledge and human mind processes.

Finally, all these observations lead to a practical and comprehensive image of the subtle ways/processes the refining knowledge is achieved in a realistic interaction with the environment, with an optimal involvement of human personality: << Knowledge, understood both as content and as schema, will therefore be constructed during this process of adaptation through its interaction with the environment.

When we are presented with data (facts, impressions), we will examine that specific information (which has some meaning and structure for us) with the knowledge that we already have. In fact, the previous knowledge will guide the type of data that we seek, or beyond that, the information we seek and are capable of understanding. If that specific information content (either know-what, why, how or who) appears in adequate conditions of motivation, interest and attention, the content will be “absorbed” into the mental model (or theory) that we are applying to that specific context. The new content might not produce much change in the structure of the mental model (alpha answer), it might produce partial modification (beta answer) or it might result in a critical modification (gamma answer, significant learning or conceptual change). These changes in our schema constitute, in fact, learning.>> Here, the subtle (vicious) circle of interdependences, we have mentioned for ICT/IS/KBS, is sensed at the core of process of refining knowledge, as we will examine that specific information (which has some meaning and structure for us) with the knowledge that we already have.

We also have to notice the pointing of the fundamental features which link knowledge with learning, but in the same time it is recognized that refining knowledge is a difficult and critical process of obtaining added value (The new content might not produce much change in the structure of the mental model), just like pearls or diamonds collecting from deepness!

Now we could better understand not only the deep relations and processes where DS/AI and ICT leverage knowledge towards the core of knowledge based society, but also the emerging trends of providing added value from that knowledge, as it is detailed in [13]:

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<<Knowledge-based society is a strategic term which – like “postmodern society“, “postindustrial society“, “experience society“, “consumer society“, “risk society“, “media society“ or “information society“ and similar terms – aims to divert attention to a certain aspect. Aspects that are particularly highlighted by the term ‘knowledge-based society’ are knowledge and education. It is said that knowledge, besides capital, will become an increasingly significant production factor of the modern society. Knowledge exists in the material form as technology. Inventiveness and science have flown into it. It is controlled by means of titles of ownership over patents and usage rights.>> If this knowledge is properly associated with human intelligence and innovative actions, as we also presented [6][15]), sometimes an added value could come from it more than from technology: “However, knowledge has also a major role in the utilization of living labor. The thesis of the knowledge-based society even claims that this role obtains an increasing significance: Many economic processes cannot be mastered any longer by the mere execution of well-defined tasks, but increasingly also through involvement and self-responsibility. In this situation, it is not a matter of having more economically independent persons but rather enabling that the dependent employees do not work in a culture of command-obedience but in one of cooperation, as well as of process and result responsibility.”

Using this idea and the digital transformation/disruption trends, we witness miracle changes of the business models, based on human potential and labor but using ICT advances with unprecedented efficiency: “An increasing number of companies are no longer oriented towards the production of mass-products, but rather towards complex system solutions which are to be found only through the utilization of the subjectivity of living labor or through living knowledge which – as opposed to materialized knowledge (in technology) – is hard to control by the employer and to a certain extent needs to be introduced voluntarily. Example: The automobile industry still produces automobiles. However, today’s task is increasingly not a matter of selling a physical product, i.e. automobile, but satisfying the customers’ mobility requirements. People do not want to necessarily own the car, but to use it in places where a bike, train or bus does not suffice. The solution of these issues – e.g. by car-sharing linked with further usage possibilities – requires communicative and logistical services that very much go beyond the manufacturing of physical products. It is a matter of communication and cooperation with customers who in a certain way become the co-producers of the mobility options“ These simple examples (opposed to materialized knowledge) could only show another iceberg tip of ICT, as we repeatedly presented [15][12][6], but indeed they forecast a new World, which will surprise us not mainly by the technology advances, but especially by the ways ICT could leverage the innovation in the modes of impacting the human thinking and using ICT when refining knowledge.

Consequently, we have to timely watch and analyse DS/AI and generally the ICT advances, in order to optimally achieve the refined knowledge that could provide the sustainable progress of KBS.

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3. Conclusions We have considered the context and the trends of the actual role/phase of ICT advances, for enabling a further World progress, in all areas, i.e., to reach a sustainable general development and in the same time avoid undesired evolutions of the Earth ecosystem challenges, like climate changes, Earth resources fading or … Covid 19 pandemic (without forgetting …food!). Observing that “evolutions” also suppose now (looking just at climate changes or Covid 19 daily consequences) a time critical race, we have emphasized the point where the ICT performances (as speed) meet the need for faster solving/processing the complex problems which actually are associated with the Data Deluge (Big Data), produced at the Earth scale, but complicatedly linking a diversity of domains. This way we have revealed the support expected from the ICT advances, where AI became the most promising instrument to face the complex problems of practically all domains, mainly by ML or DL new models and algorithms, based now on DS. Consequently, it is essential to deeper analyse how DS/AI/ICT could work together for better and faster results, providing the expected benefits on refined knowledge, but keeping low the undesired consequences such exponentially development could induce when facing challenges like climate changes and Earth resources fading (as most prominent and increasing everyday).

As concrete results of this support for AI gigantic networks, we have presented some issues regarding mechanisms and the core of the relations between the peaks of advanced processors technology and the fundamentals of their limiting factors, including the “46,225 square millimeters” chip that boasts 2.6 trillion transistors, which is in fact the maximal available (entire wafer of silicon) today. These mean that physical limits of technology and also Moore’s Law, we repeatedly have mentioned [18][12], are one of the fundamental challenges for ICT, needing revolutionary innovations in order to go on. This way it is explained why these performances are needed for the most advanced actual and future applications areas of AI, confirming the dramatic struggle of actual ICT trends, to achieve “a really big chip”, but, in the same time, the dimension of this permanent challenge.

The benefic results of AI come along with performant processing (IT), but some of the most complicate optimization problems and eventually AI applications could be found in a diversity of areas of the communications field, although here they appear less impressive than self-driving cars industry, but it is worth to recall the crucial importance and the huge dimension of communications when converging with IT in ICT. On this line, we have presented, among others, some promising AI applications, as in wireless communications and intelligent self-driving networks.

Another conclusion is that the general progress of AI/ICT is more and more depending on models and algorithms, confirming also our earlier opinion that the technology advances themselves are not enough, even with the exponential development of hard components of ICT, but they have to be applied considering at every step the refined knowledge that reflects all ICT impact consequences, the fast-changing Data Deluge and the general IS/KBS context at Earth scale. In order to find the optimal matches, a lot of work has to be done on high amounts of available (but usually unstructured) data, but this could be time and energy consuming and this way we have just arrived to the core of the relation between the processors’ performances

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and the targets of DL/ML/AI, where DS is coming with the expected support, including appropriate methods and algorithms.

Each of these methods supposes a deeper approach, which is required to provide the progress in this complex context of AI/ICT/IS/KBS, for better results against more and more difficult actual and future problems at Earth scale. Predictive causal analytics have to consider the premises/causes of involved processes evolutions we have to predict, while the prominent actual method is still represented by prescriptive analytics, as it provides the highest results we are expecting, i.e., to have the optimal decisions after analyses and prediction of the targeted process/context. For example, this method will be benefic for the self-driving cars industry, when deciding what to do in the everchanging complicate traffic processes. All these methods are important and must work together on the general context and this is also true for both machine learning for making predictions (ML-MD) and machine learning for pattern discovery (ML-PD). The applications of ML-MD are based on previous (historical records) relevant data (supervised learning), while ML-PD are following the unsupervised models, where the ML system is looking to find hidden patterns for predictions [2].

One conclusion is that ML-PD and prescriptive analytics could better support the most AI advances in the future more and more complex context to be optimized, in presence of the high levels of uncertainty.

A deeper analysis revealed, considering the first section of the paper, that the DS/AI advances have the potential to improve the general context of ICT/IS/KBS, but the maximal results should necessarily include refined knowledge on multi-criteria optimization. This way, the link between DS/AI advances and the mechanisms of refining knowledge is naturally provided by the updated cyberinfrastructure, which could provide not only the mentioned support of the technology, but also the main level (science and engineering research) and channel to create and spread knowledge and eventually refined knowledge, with maximal efficiency. Research is identified and recognized as the top level of creating and refining knowledge at World scale, it eventually pushing its results everywhere, but the point is that, this way, DS/AI, through cyberinfrastructure, could speed up and enable more efficient the progress of all human activities.

One of the most important requirements to be fulfilled in the exponential evolution of the DS/AI/ICT context, in order to get optimized solutions and refining knowledge for the actual challenges involving Big Data and other complicated problems of the Earth ecosystem is the need of standardization when developing such complex and advanced cyberinfrastructures, aiming to provide efficient interoperability and development.

For knowledge refining, other features have to be also considered, because, in all cases where human mind is involved in the Earth ecosystem (knowledge must be studied in a particular context), the role of human intelligence is and must remain fundamental even in the DS/AI advances context, including the revealed link of knowledge with learning. In the same time, it is recognized that refining knowledge is a difficult and critical process of obtaining added value, where DS/AI and ICT will leverage knowledge towards the core of knowledge-based society.

We argued that if this knowledge is properly associated with human intelligence and innovative actions, sometimes an added value could come from it more than from technology. Using this idea and the digital transformation/disruption trends, we witness

30

miracle changes of the business models, based on human potential and labor but using ICT advances with unprecedented efficiency. Presenting some simple examples, another iceberg tip of ICT was revealed, as indeed they forecast a new World, which will surprise us not mainly by the technology advances, but especially by the ways ICT could leverage the innovation in the modes of impacting the human thinking and of using ICT when refining knowledge.

Consequently, we have to timely watch and analyse DS/AI and generally the ICT advances, in order to optimally achieve the refined knowledge that could provide the sustainable progress of IS/KBS. REFERENCES [1]Samuel K. Moore, Supersize AI Cerebras’s silicon-wafer-size chip boasts 2.6 trillion transistors, IEEE Spectrum, Volume 58 / Issue 7 July 2021 [2]Hemant Sharma, What Is Data Science? A Beginner’s Guide To Data Science, https://www.edureka.co/blog/what-is-data-science/ [3]Victor Greu, Information and communications technology is merging data science and advanced artificial intelligence towards the core of knowledge based society -(Part 2), Romanian Distribution Committee (affiliated to the “International Association of the Distributive Trade”-scientific association – A.I.D.A. Brussels) Magazine(international; electronic; covered in RePEc International Data Base), Volume 12, Issue 2, Year 2021.

[4]Irena Atov, Kwang-Cheng Chen, Ahmed Kamal, Shui Yu, Data Science and Artificial Intelligence for Communications, IEEE Communications Magazine ( Volume: 58, Issue: 1, January 2020) [5]P. Cheng, Z. Chen, M. Ding, Y. Li, B. Vucetic, D. Niyato, Spectrum Intelligent Radio: Technology, Development and Future Trends, IEEE Communications Magazine ( Volume: 58, Issue: 1, January 2020) [6]Florin Enache, Victor Greu, Petrică Ciotîrnae, Florin Popescu, Model and Algorithms for Optimizing a Human Computing System Oriented to Knowledge Extraction by Use of Crowdsourcing, 2020, 13th International Conference on Communications (COMM), (Politehnica University of Bucharest, Military Technical Academy, IEEE Romania), (COMM 2020 is covered in IEEE Explore Database and ISI Web of Science in the Conference Proceedings Citation Index) [7]G. Zhu, D. Liu, Y. Du, C. You, J. Zhang, K. Huang, Toward an Intelligent Edge: Wireless Communication Meets Machine Learning, IEEE Communications Magazine ( Volume: 58, Issue: 1, January 2020) [8]H. Huang, L. Zhao, H. Huang, and S. Guo, Machine Fault Detection for Intelligent SelfDriving Networks, IEEE Communications Magazine ( Volume: 58, Issue: 1, January 2020) [9] Victor Greu, Information and communications technology is merging data science and advanced artificial intelligence towards the core of knowledge based society -(Part 1), Romanian Distribution Committee (affiliated to the “International Association of the Distributive Trade”-scientific association – A.I.D.A. Brussels) Magazine(international; electronic; covered in RePEc International Data Base), Volume 12, Issue 1, Year 2021.

[10]Daniel E. Atkins et al, Revolutionizing Science and Engineering Through Cyberinfrastructure: Report of the National Science Foundation Blue-Ribbon Advisory Panel on Cyberinfrastructure, 2003, https://www.nsf.gov/cise/sci/reports/atkins.pdf 11]Ernesto Villalba, The Concept of Knowledge for a Knowledge-based Society From knowledge to learning, European Commission Joint Research Centre © European Communities, 2007 [12]Victor Greu, The information and communications technology is driving artificial

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intelligence to leverage refined knowledge for the World sustainable development – (Part 2), Romanian Distribution Committee (affiliated to the “International Association of the Distributive Trade”-scientific association – A.I.D.A. Brussels) Magazine(international; electronic; covered in RePEc International Data Base), Volume 10, Issue 1, Year 2019.

[13]Andreas Poltermann, Education for a Knowledge-Based Society? A Concept Must be Rethought, 17 April 2014, https://rs.boell.org/en/2014/04/17/education-knowledge-basedsociety-concept-must-be-rethought [14]Victor Greu, Using the information and communications technology data deluge from a semantic perspective of a dynamic challenge: What to learn and what to ignore?

– (Part 2), Romanian Distribution Committee (affiliated to the “International Association of the Distributive Trade”-scientific association – A.I.D.A. Brussels) Magazine(international; electronic; covered in RePEc International Data Base), Volume 10, Issue 4, Year 2019.

[15]Victor Greu et all, Human and artificial intelligence driven incentive-operation model and algorithms for a multi-purpose integrated crowdsensing-crowdsourcing scalable system, Proceedings of International Conference Communications 2018, (Politehnica University of Bucharest, Military Technical Academy, IEEE Romania), June 2018(COMM 2018 is covered in IEEE Explore Database and ISI Web of Science in the Conference Proceedings Citation Index).

[16]Fran Berman, Current Working Definitions Of Cyberinfrastructure, 2005, https://www.researchgate.net/publication/49471518_What_is_Cyberinfrastructure/link/0912f 51085bdceaf0a000000/download [17]Gordon Bell, Tony Hey, Alex Szalay, Beyond the Data Deluge, Science Vol 323, 6 March 2009.

[18]Victor Greu, Searching the right tracks of new technologies in the Earth race for a balance between progress and survival, Romanian Distribution Committee (affiliated to the “International Association of the Distributive Trade”-scientific association – A.I.D.A. Brussels) Magazine (international; electronic; covered in RePEc International Data Base), Volume 3, Issue1, Year 2012.

[19] *** , IBM Watson Studio, 2021, https://www.ibm.com/cloud/watsonstudio?p1=Search&p4=43700052310836558&p5=b&gclid=CjwKCAjwiLGGBhAqEiwAgq3 q_kVnog-GfCMmo417Tjt9fX_PrUyfS3QWUVB3QD1VAg2MwYhte183BoC90gQAvD_BwE&gclsrc=aw.ds [20]E. S. Vorm, Computer-Centered Humans: Why Human-AI Interaction Research Will Be Critical to Successful AI Integration in the DoD, IEEE Intelligent Systems (Volume: 35, Issue: 4, July-Aug. 1 2020) [21] Victor Greu, Context-aware communications and IT – a new paradigm for the optimization of the information society towards the knowledge based society (Part 2), Romanian Distribution Committee (affiliated to the “International Association of the Distributive Trade”-scientific association – A.I.D.A. Brussels) Magazine (international; electronic; covered in RePEc International Data Base), Volume 5, Issue4, Year 2014.

[22] Victor Greu, Communicate on … Communications - From a Conference every 2 years to the need to communicate everyday and everywhere, Romanian Distribution Committee (affiliated to the “International Association of the Distributive Trade”-scientific association – A.I.D.A. Brussels) Magazine (international; electronic; covered in RePEc International Data Base), Volume 5, Issue 2, Year 2014

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The Increasing Adoption of Electric Vehicles (EVs) in The Last-Mile Delivery Operations

by Cosmin Tănase ABSTRACT Global demand for electric vehicles is accelerating as consumers become more eco-conscious and countries set new targets for cutting carbon emissions. The rise of e-commerce has catapulted electric vehicles to prominence. Concern about greenhouse gas emissions is driving the move away from diesel delivery vehicles towards trucks and vans using alternative power sources. Electric vehicles with a range of up to 150 miles are ideally suited to “last mile” deliveries, those with a limited radius. As global couriers and retail giants take steps to become more energy efficient, more of them are turning to electric vehicles for the last mile section of the delivery journey. Charging is one of the key considerations; substations with charging points for vehicles need to be incorporated into existing warehouse plots.

While it won’t necessarily change the structure of many existing buildings, those with more space available will be a step ahead.

Keywords: Logistics Industry, E-commerce, Delivery Speed, Electric Vehicles, Environment JEL Classification: L81, M31, 031, O33, O35 33

The recent growth of the e-commerce industry has transformed the global marketplace. According to Digital Commerce 360, consumers spent $861.02 billion on online shopping in 2020, a 44% rise over the prior year.

As digital marketplaces continue to grow, we are witnessing a shift in consumers’ demands and expectations. Today they’re looking for cost-effective yet quick delivery options.

When it comes to shipping logistics, improving the last-mile delivery process — the stage at which the parcel is delivered to the customer’s doorstep — is the most critical prerequisite in ensuring customer loyalty to online stores. But last mile-delivery service comes with its own set of challenges and hurdles.

As convenience, delivery speed, and efficiency continue to define customer experience, there is a steady growth in the use of Electric Vehicles to carry out last-mile operations. EVs are eco-friendly and offer some hidden business gains to supply chain enterprises. Over the past few years, there has been a tremendous boom in the e-commerce industry. The COVID-19 pandemic has further escalated it, causing significant shifts in consumer buying behaviors and establishing online shopping as another new normal for all of us.

The bygone year also created a massive surge in demand for same-day and next-day home deliveries, dynamic on-demand services, and hyperlocal shopping. It is only fair to say that convenience is driving customer satisfaction, now more than ever. And as convenience takes the center stage, so does the demand for fast, efficient, and consistent last-mile operations.

Having said that, there has been a steep rise in the number of vehicles on road carrying out last-mile delivery operations. This has led to an increase in carbon emissions and greater fuel consumption. The growing demand for last-mile deliveries is expected to result in 36% more delivery vehicles in the top 100 global suburbs by 2030. This is also expected to increase carbon emissions up unless effective measures are taken.

For enterprises involved in the final mile race, whether it is retail, e-commerce, direct-to-consumer selling, third-party logistics, food, and grocery deliveries, or home services, good logistics is a true litmus test for success in the marketplace.

But at the same time, as socially responsible corporates, businesses also have a commitment towards the environment — to control the devastating impacts of logistical activities on the planet and build sustainable supply chains.

Many supply chain enterprises are therefore embracing greener logistics practices with the aim of reducing carbon footprint and minimizing the impact on the environment.

E-commerce giant Amazon plans to run on 100% renewable energy by 2030 and is working with Rivian Automotive Inc. to include 100,000 battery-electric delivery vans for its Prime deliveries. In August 2020, Walmart-owned Flipkart announced its commitment to transition to 100% adoption of electric 34

vehicles by 2030, joining The Climate Group’s global electric mobility initiative, EV100. Walmart also aims to operate an entire fleet of all-electric vehicles powered with 100% renewable energy, to support their road to zero emissions by 2040.

Switching to Electric Vehicles in the Final-Mile: An Eco-Friendly Move The adoption of EVs or electric vehicles for last-mile deliveries is perhaps one of the coolest trends towards implementing green logistics in supply chains. These electric vehicles run on electric motors, instead of internal-combustion engines that generate power by burning a mix of fuel and gases.

There are two types of EVs popularly used — All-Electric Vehicles (AEVs), which run solely on electricity, and Plug-in Hybrid Electric Vehicles (PHEVs), which have both an internal combustion engine and electric motor, running partially on fuel and electricity.

Either way, EVs are seen as an effective replacement for fuel-intensive automobiles, in order to address the issue of rising pollution, global warming, and depleting natural resources. Apart from being environmentally friendly, electric vehicles also offer supply chain enterprises with many other business benefits.

Business Benefits of Using Electric Vehicles (EVs) for Last-Mile Deliveries 1. Minimal fuel consumption The logistics industry relies heavily on transportation, and that translates into excessive quantities of fuel consumption, throughout the supply chain journey. The U.S. used nearly nine billion barrels of petroleum in 2018, two-thirds of which went towards transportation. No petrol, CNG, or diesel is needed in a fully electric vehicle, and very little fuel is required even for a hybrid EV. By using electric vehicles for carrying out last-mile deliveries, supply chain enterprises can, therefore, minimize fuel consumption significantly.

2. Cost-efficient logistics It goes without saying: fuel consumption and logistics costs go hand in hand, so when you go all-electric with last-mile operations, it also reduces operating costs along with lesser fuel consumption. The operational cost of a conventional three-wheeler is 3.3 times higher than an electric three-wheeler. Over the life of the asset, it adds up to sizable cost savings. Also, with technological advancements, switching to an electric delivery fleet is no longer a huge monetary investment, as compared to a few years ago.

3. Convenient and easy to maintain Electric vehicles are quite low maintenance. Just like a smartphone, electric vehicles can be connected to an external power supply in order to recharge. Once recharged, most EVs have a mileage of 80 to 100 miles and can last up to 12 hours. Electric vehicles also have fewer auto parts compared to regular vehicles — such as the engine, a radiator, pistons, spark plugs, fuel pumps, cooling systems, exhaust systems, and timing belts, which makes vehicle maintenance a lot more hassle-free. These vehicles only 35

need a battery replacement or maintenance, once every couple of years. Research by automotive data experts KeeResources revealed that an electric car is at least 30% cheaper to service and maintain than an internal combustion-engine vehicle.

Plans of electrification of major fleet operators Fleet operators are companies that own or lease vehicles to businesses or organizations to be used in a variety of ways including the transportation of goods. Many of these large and small supply chain enterprises/fleet operators are embracing environment friendly logistic practices: •

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•

•

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E-commerce giant Amazon was one of the first to sign the Climate Pledge and made a commitment to become net carbon zero by 2040. The company has ordered 100,000 electric delivery vans from Rivian, an American electric car manufacturer, and is testing them in various locations. Amazon also ordered 1,800 electric vans from Mercedes-Benz for its European delivery fleet.

FedEx plans to electrify its entire parcel pickup and delivery fleet by 2040. Moreover, it plans to invest USD 2 billion dollars for vehicle electrification, sustainable energy, and carbon sequestration during that period. With close to 3,000 electric vehicles in service, they recently placed an order with General Motor for 500 EV600s, an electric light commercial vehicle.

UPS is investing in Arrival, a UK based electric vehicle manufacturer, and has ordered 10,000 electric vehicles to add to its fleet in North America and Europe. The initial 10,000 will roll out from 2020 to 2024 and UPS has an option for an additional 10,000 during this period. In addition, on the truck front, UPS has placed orders for 125 Tesla semi-trucks and is collaborating with Daimler Trucks to develop a Class 8 electric truck.

IKEA also has a goal of zero emission home deliveries. IKEA’s goal is to have 25% of its last mile deliveries done by electric vehicles by 2025. IKEA prioritized New York City, with 40 vehicles and the Los Angeles area with 50 trucks. To help them attain their goal, they are using Fluid Truck, an online vehicle rental platform with a fleet of electric trucks, that can be lease as needed.

In line with its sustainability goals, DHL intends to reduce all transport-related emissions to zero by 2050. With 18% of the current fleet electric, DHL plans to electrify 60% of its fleet by 2030. Recently, they accelerated their carbon neutral roadmap by investing over USD 8 billion to reduce their CO2 emissions over the next 10 years covering, not only zero-emission vehicles, but also alternative fuels for aviation and investments in climate-neutral buildings. DHL announced a partnership with Fiat EDucato for 14,000 electric vans in Europe by 2030.

Conclusions Implementing efficient last-mile delivery processes offers e-commerce brands an invaluable opportunity to adapt to changing customer demands, and differentiate their offerings from the competition. Those desiring to succeed with an online store need to confront last-mile delivery challenges proactively. And that requires the right technology, complete transparency, and smooth communications between the delivery team and your customers.

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Though the concept of electric vehicles has been around for a long time, lately it has drawn considerable interest among supply chain enterprises due to its efficiency and sustainability. But the big question is whether it is ideal for a business to adopt EVs for its last mile operations?

While all sorts of delivery businesses can easily implement an EV delivery fleet, it is most suited to businesses that perform last-mile deliveries within a fixed and limited radius — such as retail delivery, e-commerce, home service businesses, milk, groceries, or food delivery businesses, etc.

Electric vehicles are gradually gaining popularity in the final-mile game, and it is certainly a worthy investment to consider in 2021 and beyond. If a retailer further wants to optimize its supply chain above and beyond implementing EVs in the supply chain, smart route optimization powered by Artificial Intelligence can help in accurately planning delivery routes, day-to-day dispatches, while driving lesser miles and improving last-mile visibility for the business.

References [1] Brind, J. (2020) – “How Demand for Electric Vehicles Will Impact the Supply Chain” https://www.supplychainbrain.com/blogs/ [2] Gupta, A. (2021) – “Covid-19 Pandemic Acts As A Catalyst To Accelerate The Adoption Of Electric Vehicles In The Last-Mile Delivery Sector” https://inc42.com/resources [3] Karvi, R. (2020) – “EVs: The Future of Last Mile Delivery” https://www.logisticsinsider.in/ [4] Muhhamad, M. (2021) – “Last Mile Delivery Vehicles Aiming for Electrification” https://powertechresearch.com/ [5] Perryman, A. (2021) – “A growing appetite for EVs tasks the supply chain to scale” https://www.supplychaindive.com/news/ [6] Skylar, R. (2021) – “Seven Last-Mile Delivery Challenges, and How to Solve Them” https://www.supplychainbrain.com [7] Shweta, S. (2021) – “Electric Vehicles (EVs) - The Future of Last-Mile Deliveries in 2021 and Beyond” https://blog.locus.sh/ [8] Sumit, C. (2021) – “Last-mile delivery opens doors for adoption of electric vehicles” https://www.livemint.com/news/

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Challenge 21st Century, Kyrgyzstan, University of Central Punjab, Adriatic Fair, ANUGA “Transform”, ISAB Budweis, Innovation Catalyst, Duesseldofer Pallet, Digital Academic Publications, and Traditions & Visions

Prof. Dr. Bernd HALLIER

Prof. Dr. Bernd Hallier, President of the European Retail Academy (ERA: http://www.european-retail-academy.org/), an Honorary Member of the Romanian Distribution Committee, and distinguished Member of both the Editorial Board of “Romanian Distribution Committee Magazine”, and the Editorial Board of RAU “Holistic Marketing Management” brought to our attention other great events happening in the last time, and allowed us to present them. It is also worth remembering that: immediately after visiting Romania for the first time on the occasion of the 24th International Congress of the International Association for the Distributive Trade (AIDA Brussels), Prof.

Dr. Bernd Hallier sent us, in May 1998, a memorable letter we have referred initially in the Journal of the Romanian Marketing Association (AROMAR), no. 5/1998, and also later, in 2010, in the first issue of the Romanian Distribution Committee Magazine; the Romanian-American University (RAU) has awarded Prof. Dr. Bernd Hallier a “Diploma of Special Academic Merit”; the “Carol Davila” University of Medicine and Pharmacy, Bucharest, has awarded Prof. Dr. Bernd Hallier a “Diploma of Excellence”.

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Challenge 21st Century G-Global and the Eurasian Economic Club of Scientists will hold in December the Congress: “G-global World of the 21st Century”. This international project is aimed at consolidating all interested countries to improve the sustainability of the global economy, the effectiveness of its management, wide discussion and solutions to global and regional security, promoting development for investments and human capital. The Congress will be attended by the top management of the United Nations, former and current leaders of countries and governments, heads of big business, Nobel Prize winners and other global experts and world-class practitioners.

“After a century of Colonialism and after a century of big political blocks dividing the world after World War II this Congress offers the scope of a century of equal participation despite the size or history of each country and independent from its political or religious believes” Prof. Dr. Bernd Hallier (member of the Eurasian Economic Club) stated. “Taken the transformation of Kazakhstan starting from independence under the leadership of its First President N. Nazarbayev and the development with its function as a bridge in Eurasia between China and Europe, new views about Ecology by Expo 2017 it could become a World Heritageexample of global peaceful cooperation of equal partners in the 21st Century,” Hallier added. ________________________________________

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Kyrgyzstan Kyrgyzstan is organizing in November a hybrid Event: Central Asian Sustainability Forum. It is worth to be mentioned that the mentor is Prof. Dr. Mikhail Fedorov, a very good friend of Prof. Dr. Bernd Hallier. Both created together with Prof. Dr. Oleg Oshkordin and their Eurasian Youth Forum on a train-trip from Yekaterinburg/Russia to Nur Sultan/Kazakhstan a statement to found a Global Green University which was signed also by the Korean Nobel Laureate Raekwong Chung. The GGU got its own Home Site www.european-retailacademy.org/GGU designed by Dr. Alina Pukhovskaya.

“It is very important to create parallel to the revitalization of the traditional Silk Road also an academic network to promote the latest know how of Sustainability to the Stan-countries like Pakistan, Tadjikistan, Kyrgyzstan, Kazakhstan, and Uzbekistan. We need this cross-border dialogue because there is only one world which we share all together independently of our local/regional political views or religious believes.” Prof. Dr. Bernd Hallier stated as a welcome address to the Central Asian Sustainability Forum. ________________________________________

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University of Central Punjab The UCP Business School of the University of Central Punjab, Lahore in Pakistan becomes the latest member of the European Retail Academy as Prof. Dr. Bernd Hallier informed his network welcoming this step to tighten also the strings to Asia.

The UCP Business School will organize its 7th International Conference on Contemporary Issues in Business Management with the topic “Emerging Business Opportunities and Challenges: Covid 19 Perspective”. The Event will be digitally offered at Nov. 22nd/23rd 2021, more Website address: (“See page ”). ________________________________________

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Adriatic Fair The Adriatic Fair in Budva/Montenegro is seen by Prof. Dr. Bernd Hallier not only as a business meeting but also as a geopolitical key of understanding : “It is as well a chance to interconnect the territories of the former Jugoslavia as also the West-Balkan with the European Union” ( see Interview YouTube Budva)

Budva was also the starting point of the Pan Balkan Initiative of Prof. Hallier and Prof.

Zaric. The ERA-professors see a lot of the controversial discussions in today's politics based on the not solved problems of the time of the clashes between the Oriental Osman Empire and the Austrian-Hungarian Habsburg Monarchy (“See You Tube PBI ”). Both hope to contribute by their cross border academic networks to improve relations by exchanges of students and teachers.

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ANUGA “Transform” The world leading food exhibition ANUGA was founded in Germany in 1919. Today it is hold bi-annually in Cologne with exhibitors from about 100 countries around the world. In 2017 the founders of the Thematic University Network Food did choose Anuga for its launch (see more: Link lecture Violena Nencheva).

The 2021 motto is “Transform” and is aiming to different aspects: physical + Anuga@Home ... new Food ... Sustainability in Food Production and Distribution ... Animal Well-Being. For Prof. Dr. Bernd Hallier this event is again also “Food for Thought”; branding an exhibition over a period of more than 100 years - while adjusting its content and communication permanently to the present and future demand. _______________________________________

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ISAB Budweis The Faculty of Economics, University of South Bohemia in Ceske Budejovice/CZ has established an International Advisory Board. The first members being appointed are the Professors H. Pernsteiner/Austria, B. Hallier/Germany, L. Sdrolias/Greece, Z. Bacsi/Hungary, R. Miura/Japan, A. Skibiński/Poland and E. Horska/Slovakia.

Prof. Dr. Bernd Hallier has been teaching in Budweis periodically after the transformation of the Czech Republic. In 2009 his Budweis-Students created the see page after a crash course about city marketing. Budweis University also took part with three students sailing in an international workshop of Prof. Dr. Bernd Hallier with the tall-ship Kruzenshtern from Kaliningrad/Russia via the Skagarak to Bremerhaven/Germany. The focus was beside speaking English and acting in an international team also character-building by climbing the masts of the boat or to build an emergency-team for the case of SOS. ________________________________________

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Innovation Catalyst The success of the “Duesseldorfer Pallet” in 1985/86 was for the ISB (later transformed to the DHI Deutsches Handelsinstitut) the start for sustainable packaging and logistics competences. Testimonials for DHI-Innovations came from companies like Chep, Coca Cola, the Corrugated Industry, Kaufland-Group, Krings and Metro as well as from the German Federal Minister for the Environment Prof. Dr. Klaus Töpfer. Trade had been positioned by ISB/DHI initiatives to be seen by the public as a driver for innovation for the Total Supply Chain.

For Prof. Dr. Bernd Hallier as the managing director of ISB/DHI at that time the accumulation of innovative micro-economic processes to increase efficiency/productivity is finally resulting in the macro-economic growth of the Wealth of Nations. “It is not always a big thought breaking the routine - needed for the success of Applied Sciences and connected Businesses but the sustainable process of permanent innovation in the daily operations which makes the difference of companies: Retail is Detail!” Hallier summarizes the international success of the German discounters Aldi and Lidl. ________________________________________

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Duesseldofer Pallet Becoming managing director of the Institute for Self-Service (ISB later DHI /EHI) in the beginning of 1985 Bernd Hallier’s first innovation-project was the Duesseldorf Pallet: a standardized half-size Euro-Pallet. “The initiator in that logistics-team was Walter Vieth - one of the first ALDI-managers and totally fixed on quick turnover and low costs" Prof. Dr. Bernd Hallier remembers. “Also, for this technical development we used the push and pull-strategy for market introduction: in the beginning of 1986 the magazine Pack Report estimated already 120.000 of our pallets in circulation in Germany”.

“The name derived from the location of our agreement with retailers about this tool of rationalization: a pub in Duesseldorf! The key for the success was the idea + team for getting volume by integrating as many retailers as possible: Applied Sciences is a combination of Innovation and Motivation” Hallier summarized. About 5 years later the Chep-pool supported the renting of the ISB/EHI pallet in connection with the new German environmental focus: Chep claimed to save per year 200.000 tons of waste in the Total Supply Chain by this multi-trip pallet. ________________________________________

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Digital Academic Publications “Prof. Dr. Theodor Purcarea from the Romanian American University (RAU) in Bucharest is already for years within the group of ERA-professors by the digital publication of Holistic Marketing Management the pioneer for modern social media cross-border” Prof. Dr. Bernd Hallier stated in an evaluation of changes in University Life of the last years due to Corona. “So, he earns not only that reputation but also that one of mastering the Covid challenges quicker than others”.

“Additionally, he became a bridge-builder in Romania for applied sciences due to his MAGAZINE published digitally for the Romanian Distribution Committee” Hallier added. “The Volume 12, Issue 2/2021 shows excellently the inter-connectivity of knowledge exchange with the Association of Faculties of Economics in Romania (AFER) as well as with the Total Supply Chain”.

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Traditions & Visions While according to Prof. Dr. Bernd Hallier at school and for the BA-degree mainly “learning” is essential - for MA and PhD degrees the “inspiration” is becoming the main factor for success. Human Intelligence differs to AI in the additing of “emotion” to the input of “ratio”.

In a review about the history of the European Retail Academy he focused two events where emotions of “tradition” influenced the success story of the ERA-researchers. “The academic lifestyle of behavior plus architecture of the Templeton College impressed our study group at the invitation of Prof. Dr. Ross Davies (see also Hall of Fame 2008) in Oxford very much” Prof. Dr. Bernd Hallier remembers. “The flair/ spirit loci united our international expert team and became a driver of our team-spirit.”

“A similar thrill was created at the Annual Meeting in 2011 at the award-ceremony of the VSE Prague by the Gaudeamus Igitur of the student chorus, the fanfares and the robes of the participating professors” (see YouTube VSE Prague). “Suddenly it was not just a meeting as an activity at that day - but the feeling was created that the audience had been part of a long string in a historical process: which again became a source of inspiration/vision for the development of future tasks - Especially in the disruptions by Corona it becomes obvious how much such interpersonal feelings are missed as a stimulus for the present student-community being limited to digital events” Prof. Dr. Bernd Hallier concluded. ________________________________________

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● Tudoriţa ALBU – “Bocet în Arcadia”. Profesor George SORESCU, Personalitate complexă (Dirge in Arcadia) Note from the Editor-in-Chief As we remembered on another occasion, Dr. Tudorita ALBU, is continuing to advocate the national values (the passion for the recovery of these values and promoting the authentic being obvious). That is why it is our honor to share with our Readers her new thoughts about a great Teacher, Dr. Tudorita ALBU being deeply grateful to have known such a unique person like Professor George SORESCU, who passed away on April 2, 2021. Professor George SORESCU was the Mentor of his little brother Marin SORESCU (the little brother being: a valuable Romanian poet and playwright, recipient of the International Herder Prize, granted by the University of Vienna in 1991 for his entire activity; nominated for the Nobel Prize for Literature in 1996, when he died at age 60 from a heart attack).

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Prof. Dr. Tudoriţa ALBU – “Bocet în Arcadia”, Profesorul George SORESCU, Personalitate complexă

În credința românească, fiecare copil primește la naștere o stea, care strălucește pe bolta cerească atâta vreme cât trăiește un om, iar când îi cade steaua, i se curmă viața.

Printre multele stele care cad zilnic, pe 2 aprilie 2021 a mai căzut o stea, aceea care a vegheat, timp de 93 de ani spiritul celui care a fost Omul George Sorescu.

S-a născut la 23 septembrie 1927, în comuna Bulzești (Dolj), nume de sorginte ardelenească, după cum ardeleni au fost locuitorii comunei, veniți prin transhumanță din Mărginimea Sibiului. Numele comunei a căpătat notorietate, intrând în istoria literară datorită lui Marin Sorescu, care, în epopeea universului rural ”La Lilieci” a reușit să surprindă o lume văzută în structurile ei existențiale, crâmpeie de viață, ”un altar în timp, în care cugetul autohton se rostogolește, se încifrează și se dezvăluie” (George Sorescu).

Prestigios cadru didactic universitar, poet, prozator, critic literar, cercetător, traducător, latinist, eminescolog, filofrancez, ale cărui lucrări de specialitate alcătuiesc un veritabil tezaur cultural, George Sorescu ni se relevă ca o personalitate marcantă a vieții culturale naționale.

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Respectul pentru familie și pentru valorile perene ale vieții sătești l-a legat afectiv pe George Sorescu de cadrul pitoresc al comunei sale natale, ”Arcadia” sufletului său, cum însuși o numea (AXIS MUNDI, cum ar spune latinul), determinându-l să rezoneze permanent și să se inspire din acest izvor nesecat de fericire, o fericire absolută, un fel de rai pământesc, cu oameni de o mare puritate sufletească. Trăia permanent cu nostalgia momentelor din viață petrecute cu maximă intensitate și bucurie, evocând de fiecare dată evenimente irepetabile și ireversibile. În trecerea implacabilă a timpului, fusul toarce din ”Furca vremii ce-nfășoară/ Caierul alb cu firul/ Ud” („Stau și mă-ntreb”) și vine o vreme când se termină totul, vine acea clipă unică în care rămâne din om (spirit, trup și suflet) doar ”un colțișor de poveste”. Lăsând în urmă, ca un semn al trecerii sale, doar ceea ce a construit, omul rămâne în amintirea altora așa cum a știut el să se definească.

Omul George Sorescu rămâne în amintirile noastre drept un exemplu de profesionalism, o viață închinată Cuvântului, exemplu de omenie. A plecat dintre noi pe alt tărâm, din lumea cu dor în lumea fără dor, să se odihnească alături de toți cei dragi plecați mai devreme: mama, Nicolina Sorescu - ”Altar în care mă închin/ de trei ori:/ în zori,/ în amiază`/ și-n chindii” („Mama”); tata, Ștefan I. Sorescu, pentru care ”Plâng frunze de ani pe/ Poteci/ Și potecile plâng/ În hotar, izvoarele zilei/ Sunt seci/ Luceferi pe boltă/ Sunt reci” ( „De ani, poteci”); bunica ”înaltă, frumoasă și /tăcută Marie!” ( „Portret”); fratele, Marin Sorescu – ”O vie pecete/ Cu fără de seamăn/ Simboluri-idei,/ Cu lumi în vârtej,/ Cu rustice dansuri,/ Cu iele,/ Aruncată-nadins într-un vis,/ Și peste sufletul meu/ Și pe cărările mele” ( „Nu l-am văzut...”).

Trecerea timpului și iminența morții au fost teme care l-au preocupat. Necontenitul contact cu natura, care îi generează imagini poetice de o rară sensibilitate, face ca existența întreagă a omului să se transforme într-un basm. Vraja ce a cuprins cândva „Coroanele de smarald/ Ale copilăriei mele/ Se destramă ... Într-o nopate de taină,/ Când mă voi preface într-un ulm/ Cu toate crengile albe.” („Cândva, demult...”) sau, vorbind despre antagonismul viațămoarte “Între porțile zilei/ Și porțile nopții/ Basmele se desfiră mereu,/ Să stea de vorbă cu Viața./ Când se vor risipi turmele,/ Un călător/ Va sta de vorbă cu Veșnicia” („Dialog”). ...Și din această viață tumultuoasă, ce poate să-i rămână omului? Făcând apel tot la imaginea poetică, George Sorescu răspunde: “Ce poate să-ți rămână/ Ție/ Dintr-al pădurilor/ Tumult?/ Semne uitate pe-o/ Hârtie,/ Murmur pierdut de / Poezie/ ... Cântec rostogolit mereu,/ Fâșii de cer, suișul greu...” („Te-ntrebi și tu”). În cimitirul Săliște (nume cu o rezonanță ardelenească, de asemenea!), înconjurat de un gard de lilieci - devenit mai târziu, conform expresiei lui Marin Sorescu, „la Lilieci” - își doarme somnul de veci George Sorescu: ”Un voievod bătrân/ Visează sub lespede/ Și nu mai știe cum îl cheamă./ Ce somn mă destramă?” („Somn”). În temeiul aceleiași rezonanțe cu natura, „Prin pădurile lumii, arar,/ Va străbate un pas neștiut/ De-al iubirii fior. În hotar,/ Eu, sub luceferi, tăcut” ( „Dincolo”).

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Aceeași Natură va fi cea care va consemna și va fi sensibilizată de dispariția omului: ”Plâng cântecele mele în spini/ Cu frunțile îndoliate,/ Cresc umbre-n albele grădini” („Plâng cântecele...”), ”Fiecare deal, / Fiecare livadă,/ Fiecare pădure/ Sună ca un cântec arcadic.” („Ultim mesaj”), rostind suferința supremă: ”A-u! Uu! U…!” ( „Bocet în Arcadia”).

Viața de dincolo este percepută asemeni unui turn, în care ”O fereastră se deschide/ Spre iad,/ Alta spre rai...”, iar „Fiecare spirală/ Va păstra pentru ziua de-apoi/ Numai umbrele pașilor.” („Turn”). Conștient de ireversibilitatea lucrurilor, omul este înclinat spre reflecție: ”Cel puțin să dormim/ În umbra unor aripi,/ Sărutate pe rând/ De solii cu o mie de fețe/ Ai timpului veșnic!” („Zbor”). „La Lilieci/ Dorm morții mei/ Pe veci;/ Călcau cândva ca mine/ Pe poteci./ (…)La Lilieci nu-i cântec/ Și nu-i gând,/ E-un somn adânc/ Sub bulgării de humă; Morții-nfrățiți cu-ntâia/ Mumă,/ De-i mai chemăm,/ Nu mai răspund” („La Lilieci”).

George Sorescu, nu numai că reflecta asupra vieții și morții, privea totuși cu ironie și umor acest ultim moment. Într-o corespondență foarte apropiată de momentul trecerii sale la cele veşnice (decembrie 2020), îmi scria:

Cu același umor privea și fratele său, Marin, moartea: “În cimitir doar deșteptarea/ Este mai grea. Încolo...trai!” („În cimitir”), iar despre sentimentul efemerității vieții, același poet scria: „Noi ne-am scris sufletul/ Pe frunze.../ Codrule,/ Dă-mi toate frunzele tale/ Să cânt cu ele/ Sau mai bine cântă tu/ Și cu sufletul meu” ( „Foaie verde”). *** Personalitate complexă, Profesorul George Sorescu a dat dovadă de o rară modestie, refuzând de cele mai multe ori să vorbească despre sine, iar dacă totuși făcea acest lucru, vorbea

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cu o neasemuită simplitate, de parcă l-am fi auzit pe Grigore Vieru vorbind despre sine: „Sunt iarbă, mai simplu nu pot fi”.

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● Professor Gheorghe ZAMAN,

Corresponding Member of the Romanian Academy

Note from the Editor-in-Chief Professor Gheorghe Zaman, PhD, Chairman of the Group of Experts of the Romanian Distribution Committee, Honorary Member, and Member of the Board of the Romanian Distribution Committee, passed away on October 8, 2021. It is a tremendous loss for the academic world, but also for all those who knew him.

Corresponding Member of the Romanian Academy, Director of the Institute for National Economy (IEN, the oldest public settlement of economic research in Romania), Honorary Member of the Association of Faculties of Economics in Romania (AFER), President of the General Association of Economists from Romania (AGER), President of the Scientific Council of Romanian Scientific Management Society (SSMAR), Professor Gheorghe Zaman was a real „design thinker” (confirming this concept introduced by Professor Roger Martin), proving an evident passion for the dynamic interplay of balancing analytical mastery and intuitive originality, and advancing step by step through the “knowledge funnel”, growing the productivity and dropping the costs, and inviting all of us to join the avenue of economic research, to integrate both, the team’s research with belief and the new knowledge obtained with the application of this new knowledge. One can say that this was a natural fact for someone specialized in the field of economic-mathematical modeling of consumption at the „Department of Applied Economics”, Cambridge University, England since 1969, under the direction of Nobel Prize in Economic Sciences Laureate Richard Stone (awarded in 1984 „for having made fundamental contributions to the development of systems of national accounts and hence greatly improved the basis for empirical economic analysis”), Joan Robinson, Maurice Dobb, and Nicholas Kaldor.

With great sadness, the Romanian Distribution Committee announced the tremendous loss on October 9, 2021: https://www.crd-aida.ro/2021/10/profesorulgheorghe-zaman-membru-corespondent-al-academiei-romane/

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Professor Gheorghe ZAMAN, Corresponding Member of the Romanian Academy

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Profesorul Gheorghe Zaman, Membru corespondent al Academiei Române

Coordonatorul Grupului de experţi al Asociaţei ştiinţifice Comitetul Român al Distribuţiei (https://www.crd-aida.ro/our-team/gheorghe-zaman/ ), Profesorul Gheorghe Zaman – Membru corespondent al Academiei Române (https://acad.ro/commem/docImg2021/n1008-GheorgheZaman.pdf ), Directorul Institutului de Economie Naţională (http://www.ince.ro/Necrolog%20Gheorghe%20Zaman.pdf ), Membru de onoare al Asociaţiei Facultăţilor de Economie din România, AFER (https://afer.ase.ro/?p=1271 ) – a prezentat la începutul unei dezbateri organizată în primavara anului 2010 în cadrul Comisiei Academiei Române pentru Studii Prospective (Moderatorul dezbaterii fiind Valeriu Ioan-Franc: https://www.crdaida.ro/our-team/valeriu-ioan-franc-2/ ) o analiză cuprinzătoare a cărţii “Lebăda Neagră: Impactul foarte improbabilului” (Taleb, N. N., 2007. The Black Swan: The Impact of the Highly Improbable, Random House Publishing Group). După cum este cunoscut, termenul “Lebăda Neagră”, inventat de autorul cărţii menţionate (Nicholas Taleb, Profesor de ingineria riscului la Institutul Politehnic al Universităţii din New York), reprezintă un eveniment neaşteptat, imprevizibil şi cu un impact enorm, pe care-l explicăm ca fiind mai puţin întâmplător şi mult mai previzibil decât a fost în realitate). Cu ocazia prestigioasei Conferințe Internaționale ESPERA 2020 s-a făcut trimitere şi la acest moment din semnificativa dezbatere. Într-un articol publicat în luna aprilie 2021 (http://holisticmarketingmanagement.ro/RePEc/hmm/v11i1/3.pdf ) s-a mai facut trimitere şi la abordarea vizionară, riguroasă, din anul 1993, de către Directorul Institutului de Economie Naţională, a problematicii privatizării în ţara noastră – “Privatizarea în România. Realizări, dileme, dificultăţi”, publicată în “Romanian Journal of Economics” – precum şi (printre alte aspecte) la evidenţierea în Revista “Tribuna Economică” nr. 18/3 mai 2000 a Simpozionului “Economia de idei şi dezvoltarea durabilă” organizat de către Comitetul Român al Distribuţiei, la Clubul Parlamentarilor Români, Palatul Parlamentului, în ziua de 16 mai 2000, Moderatorul fiind Profesorul Gheorghe Zaman.

Dincolo de cele confirmate şi de dezbateri mai recente (cu implicarea Profesorilor Gheorghe Zaman, Valeriu Ioan-Franc, Nicolae Istudor, Ion Bulborea, Moisă Altăr, Virgil Popa, Nicolae Albu, Costel Negricea, Costel Stanciu şi alţii, a se vedea: https://www.crd-aida.ro/2021/02/dezbaterelectii-de-retinut-studiul-istoriei-economice-si-importanta-intelegerii-trecutului/ ), se cuvine a aminti că doar în urmă cu câţiva ani subliniam modelul reprezentat de Profesorul Gheorghe Zaman, un călător neobosit printr-o viață de muncă, cu respect față de valorile izvorâte din spiritul poporului la care se raporta neîncetat, autoîncurajându-se prin grija sa proverbială față de economia națională şi invitând în mod constant la deschideri de orizonturi proprii care să se întâlnească cu orizontul economiei naționale ca gest al datoriei noastre comune, exprimându-şi tranşant regretul în legătură fie cu vremea irosită de alții prin discuții fără miez, fie cu aşa-zisele “idei” aruncate pe “piața relevantă”, “idei” care pot deveni nocive tocmai pentru faptul că, uneori, nu se văd prea bine şi nu se percep la timp ca periculozitate. Domnia Sa era preocupat în mod efectiv pentru economia durabilă, resimţind presiunea responsabilităţii identificării limbajului comun public-

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privat necesar acţiunii ferme la interfaţa dintre societatea cunoaşterii şi dezvoltarea durabilă confruntată cu soluţionarea, în acelaşi timp, a problemelor economice, sociale şi de mediu, continuȃnd să invite cu eleganță la lucrul în reţea naţională, exprimându-şi convingerea sporirii gradului de coeziune socială. Este binecunoscută pledoaria Profesorului Gheorghe Zaman pentru: inteligenţă economică în calitate de prioritate a politicii de competitivitate industrială şi de inovaţie, inteligenţă economică şi concurenţială la nivel microeconomic urmărind sprijinirea planificării strategice şi a procesului decizional; nevoia identificării a ceea ce este dincolo de tradiţia existentă a practicii, pentru progresul obţinut ca realizare comună, pentru asimilarea paradigmei raţionalităţii instrumentale şi crearea de competenţe şi corectă reprezentare a realităţii economico-sociale presante.

Mereu disponibil pentru comunicarea necesară pătrunderii în esenţa unei problematici abordate, Profesorul Gheorghe Zaman a păşit cu grație pe calea timpului, oferindu-ne privilegiul de a ne bucura de prietenia dăruită cu generozitate ca bază a unui dialog peren. Întotdeauna “iscoditor” cu spirit critic, Profesorul Gheorghe Zaman a fost expresia exigenței asumării libertății ştiințifice interioare de a identifica corespondențe în lumea ştiințifică exterioară care să ofere puncte de sprijin pentru noi urcuşuri pe treptele reflecţiei şi ale acțiunii, făcând dovada permanentei disponibilităţi pentru lucrul în echipa guvernată de valori şi principii, reflectȃnd şi acționȃnd cu pasiune, competență şi perseverență în pregătirea continuă a minții pentru societatea cunoaşterii.

Dumnezeu să-l ierte și să-l odihnească şi veșnică să-i fie pomenirea!

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It is a tremendous loss for the academic world, but also for all those who knew Professor Gheorghe Zaman, PhD, Chairman of the Group of Experts of the Romanian Distribution Committee, Honorary Member, and Member of the Board of the Romanian Distribution Committee.

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